CLIAMS:We Claim:
1. A method of automatic assessment of a candidate by a virtual interviewing system, the method comprising:
receiving, by a processor of the virtual interviewing system, profile information associated with one or more candidates and job description details associated with job;
identifying, by the processor, a plurality of expertise areas of the one or more candidates from the received profile information matching with the job description details;
providing, by the processor, a plurality of questions to the candidate corresponding to the identified plurality of expertise areas;
determining, by the processor, a score for the plurality of questions in real time upon evaluating response of the one or more candidates based on one or more model answers stored in a knowledge repository of the virtual interviewing system; and
ranking, by the processor, the one or more candidates based on the score obtained and selecting one or more qualified candidates having maximum score.
2. The method as claimed in claim 1, further comprising:
creating a knowledge repository comprising at least the plurality of expertise areas, the plurality of questions related to each expertise area, the one or more model answers corresponding to the plurality of questions, and a corresponding score for the one or more model answers; and
storing job description details associated with the job based on expertise areas required, associated competency level and weightage score assigned to the expertise areas in the knowledge repository thus created.
3. The method as claimed in claim 1, wherein providing the plurality of questions comprising:
determining order and count of the plurality of questions based on the weightage assigned in the job description details provided by a recruiter;
determining level of complexity of questions based on the associated competency level of the job description details;
providing the plurality of questions based on the complexity level; and
dynamically modifying the complexity level of questions based on the response received from the candidate to the plurality of questions.
4. The method as claimed in claim 1, wherein the plurality of questions are selected from at least one category of multiple choice questions, code correction based questions, short answer type questions, open ended questions, relationship-based questions, and single word-phrase answer questions and so on.
5. The method as claimed in claim 1, wherein determining the score for the plurality of questions comprising:
receiving answers corresponding to the plurality of questions of at least one category; and
determining the score by comparing the received answers with the model answers previously determined and stored in the knowledge repository.
6. The method as claimed in claim 1, further comprising:
determining as to whether a follow-up question is needed based on the evaluation of the answers received from the one or more candidates;
providing the follow-up question based on the determination and receiving the answers corresponding to the follow-up question;
determining as to whether a plurality of additional probing questions is needed on the same expertise area if the candidate’s answer indicates additional probing; and
rendering the plurality of additional probing questions to the candidate upon determination.
7. The method as claimed in claim 1, wherein the score is determined based on the score of the one or more candidate in each expertise area, weighted average across the plurality of expertise areas, number of follow-up questions, evaluation of answers to additional probing questions, time taken to answer the plurality of questions.
8. The method as claimed in claim 1, further comprising updating the knowledge repository based on the answers provided by the candidate to the plurality of questions and associated score.
9. A virtual interviewing system for automatic assessment of a candidate, comprising:
a processor;
a knowledge repository coupled with the processor and configured to store at least a question base and job description details associated with the job provided by the recruiter; and
a memory disposed in communication with the processor and storing processor-executable instructions, the instructions comprising instructions to:
receive profile information associated with one or more candidates and job description details associated with job;
identify a plurality of expertise areas of the one or more candidates from the received profile information matching with the job description details;
provide a plurality of questions to the candidate selected from the plurality of matching expertise areas;
determine a score for the plurality of questions in real time upon evaluating response of the one or more candidates based on one or more model answers stored in the knowledge repository of the virtual interviewing system; and
rank the one or more candidates based on the score obtained and selecting the one or more qualified candidates having maximum score.
10. The system as claimed in claim 9, wherein the processor is configured to:
create a knowledge repository comprising at least the plurality of expertise areas, the plurality of questions related to each expertise area, the one or more model answers corresponding to the plurality of questions, and a corresponding score for the one or more model answers; and
store job description details associated with the job based on expertise areas required, associated competency level and weightage score assigned to the expertise areas in the knowledge repository thus created.
11. The system as claimed in claim 9, wherein the processor is configured to provide the plurality of questions selected from at least one category of multiple choice questions, code correction based questions, short answer type questions, open ended questions, relationship-based questions, single word/phrase answer questions and so on, by performing the steps of:
determining order and count of the plurality of questions based on the weightage assigned in the job description details provided by a recruiter;
determining level of complexity of questions based on the associated competency level of the job description details;
providing the plurality of questions based on the complexity level; and
dynamically modifying the complexity level of questions based on the response received from the candidate to the plurality of questions.
12. The system as claimed in claim 9, wherein the processor is configured to determine the score for the plurality of questions by the steps of:
receiving answers corresponding to the plurality of questions of at least one category; and
determining the score by comparing the received answers with the model answers previously determined and stored in the knowledge repository.
13. The system as claimed in claim 9, wherein the processor is further configured to:
determine as to whether a follow-up question is needed based on the evaluation of the answers received from the one or more candidates;
provide the follow-up question based on the determination and receive the answers corresponding to the follow-up question;
determine as to whether a plurality of additional probing questions is needed on the same expertise area if the candidate’s answer indicates additional probing; and
render the plurality of additional probing questions to the candidate upon determination.
14. The system as claimed in claim 9, wherein the processor is configured to determine the score based on the score of the one or more candidate in each expertise area, weighted average across the plurality of expertise areas, number of follow-up questions, evaluation of answers to additional probing questions, time taken to answer the plurality of questions.
15. The system as claimed in claim 9, wherein the processor is further configured to update the knowledge repository based on the answers provided by the candidate to the plurality of questions and associated score.
16. A non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor cause a system to perform acts of:
receiving profile information associated with one or more candidates and job description details associated with job;
identifying a plurality of expertise areas of the one or more candidates from the received profile information matching with the job description details;
providing a plurality of questions to the candidate selected from the plurality of matching expertise areas;
determining a score for the plurality of questions in real time upon evaluating response of the one or more candidates based on one or more model answers stored in a knowledge repository of the virtual interviewing system; and
ranking the one or more candidates based on the score obtained and selecting the one or more qualified candidates having maximum score.

Dated this 12th day of June, 2015

M.S. Devi
Of K&S Partners
Agent for the Applicant
,TagSPECI:FIELD OF THE DISCLOSURE
The present subject matter is related, in general to assessment system, and more particularly, but not exclusively to method and a virtual interviewing system for automatic assessment of a candidate.